JIPS (한국정보처리학회)
Current Result Document :
| 한글제목(Korean Title) |
Fuzzy-Membership Based Writer Identification from Handwritten Devnagari Script |
| 영문제목(English Title) |
Fuzzy-Membership Based Writer Identification from Handwritten Devnagari Script |
| 저자(Author) |
Rajiv Kumar
Kiran Kumar Ravulakollu
Rajesh Bhat
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| 원문수록처(Citation) |
VOL 13 NO. 04 PP. 0893 ~ 0913 (2017. 08) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
The handwriting based person identification systems use their designer’s perceived structural properties of handwriting as features. In this paper, we present a system that uses those structural properties as features that graphologists and expert handwriting analyzers use for determining the writer’s personality traits and for making other assessments. The advantage of these features is that their definition is based on sound historical knowledge (i.e., the knowledge discovered by graphologists, psychiatrists, forensic experts, and experts of other domains in analyzing the relationships between handwritten stroke characteristics and the phenomena that imbeds individuality in stroke). Hence, each stroke characteristic reflects a personality trait. We have measured the effectiveness of these features on a subset of handwritten Devnagari and Latin script datasets from the Center for Pattern Analysis and Recognition (CPAR-2012), which were written by 100 people where each person wrote three samples of the Devnagari and Latin text that we have designed for our experiments. The experiment yielded 100% correct identification on the training set. However, we observed an 88% and 89% correct identification rate when we experimented with 200 training samples and 100 test samples on handwritten Devnagari and Latin text. By introducing the majority voting based rejection criteria, the identification accuracy increased to 97% on both script sets.
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| 키워드(Keyword) |
CPAR-2012
Devnagari
Fuzzy Membership
Handwritten Script
Writer Identification
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| 파일첨부 |
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